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Comparison · 2 models · Updated Oct 4, 2026

DeepSeek-V3.1 vs GPT-5 Nano

GPT-5 Nano comes out ahead, 70 to 55 on our weighted score, and it is the cheaper option too.

  1. DeepSeek

    DeepSeek-V3.1

    Released Aug 21, 2025

    55/100
    • ECI139.9
    • Price$0.385 / $1.25
    • Context131K
    Full specs Remove DeepSeek-V3.1
  2. Our pick

    OpenAI

    GPT-5 Nano

    Released Aug 7, 2025

    70/100
    • ECI139.4
    • Price$0.05 / $0.40
    • Context400K
    Full specs Remove GPT-5 Nano

  3. Add a model

    Make it a three-way comparison.

01 — Verdict

GPT-5 Nano is our pick

GPT-5 Nano is the better all-round choice, scoring 70/100 against DeepSeek-V3.1 (55). It leads on price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

  • CapabilityDeepSeek-V3.1Capabilities Index (ECI): DeepSeek-V3.1 139.9 · GPT-5 Nano 139.4
  • Lowest priceGPT-5 NanoGPT-5 Nano $0.138 · DeepSeek-V3.1 $0.601 per 1M tokens (3:1 blend)
  • Longest contextGPT-5 NanoGPT-5 Nano 400,000 · DeepSeek-V3.1 131,072 tokens
  • Widest inputsGPT-5 NanoDeepSeek-V3.1: Text · GPT-5 Nano: Text, Images
  • Self-hostingDeepSeek-V3.1Publishes downloadable weights (MIT License)
How the score is built
MeasureWeightDeepSeek-V3.1GPT-5 Nano
CapabilityCapabilities Index (ECI)50%6565
Price25%6091
Inputs & features15%3570
Context window10%2444
Overall100%55/10070/100
02 — Side by side

Every spec in one table

Highlighted cells lead their row. Dashes mean the data is not published.

DeepSeek-V3.1 vs GPT-5 Nano specifications side by side
SpecificationDeepSeek-V3.1DeepSeekGPT-5 NanoOpenAI
Capability
Capabilities Index (ECI)139.9 (best)139.4
ECI rank#100 of 148 (best)#102 of 148
GPQA DiamondGraduate-level science questions—69.4%
FrontierMath Tiers 1–3Research-level mathematics—20.0%
OTIS Mock AIME 2024–2025Competition mathematics—81.1%
SimpleQA VerifiedShort factual questions—11.7%
Price per million tokens
Input$0.385$0.05 (best)
Output$1.25$0.40 (best)
Cached input—$0.005
Blended (3:1)$0.601$0.138 (best)
Long-context rateSame rateSame rate
Price sourceMedian of 8 providersOfficial OpenAI API
Limits
Context window131,072 tokens400,000 tokens (best)
Max output8,192 tokens128,000 tokens (best)
Inputs and features
TextYesYes
ImagesNoYes
PDFsNoNo
AudioNoNo
VideoNoNo
ReasoningYesYesminimal · low · medium · high
Tool callingYesYes
Structured outputNoYes
Availability
WeightsOpenMIT LicenseProprietary
API model ID—gpt-5-nano
API providers821 (best)
ReleasedAug 21, 2025Aug 7, 2025
Knowledge cutoff—May 30, 2024
03 — Cost

What would a month cost?

Enter your expected volume in millions of tokens. List prices only; caching and batch discounts would lower these.

  • DeepSeek-V3.1$6.35
  • GPT-5 Nano$1.30
04 — Questions

Which should you choose?

Which is better: DeepSeek-V3.1 or GPT-5 Nano?

GPT-5 Nano is the better all-round choice, scoring 70/100 against DeepSeek-V3.1 (55). It leads on price, inputs & features and context window. The score weighs capability 50%, price 25%, inputs & features 15%, context window 10%.

Which is cheaper, DeepSeek-V3.1 or GPT-5 Nano?

GPT-5 Nano is cheaper at $0.05 input / $0.40 output per million tokens (official OpenAI API price). DeepSeek-V3.1 costs $0.385 input / $1.25 output per million tokens (median across 8 API providers). At a typical mix of three input tokens to one output token, that is $0.138 per million tokens for GPT-5 Nano versus $0.601 for DeepSeek-V3.1 (4.4× as much).

Which scores higher on benchmarks?

DeepSeek-V3.1 scores higher on the Capabilities Index (ECI): DeepSeek-V3.1 139.9 (#100 of 148) and GPT-5 Nano 139.4 (#102 of 148). The confidence ranges of the top two overlap (136.1–143.3 vs 134.9–141.7), so treat the gap as small.

Which is better for coding?

There are no published SWE-bench Verified results for DeepSeek-V3.1 and GPT-5 Nano yet, so there is no like-for-like coding score. On overall capability, DeepSeek-V3.1 leads, which tends to carry over to coding, but test on your own codebase. Both support tool calling for agent workflows.

Which has the bigger context window?

GPT-5 Nano has the largest context window at 400,000 tokens, against 131,072 for DeepSeek-V3.1. Maximum output per response: DeepSeek-V3.1 up to 8,192, GPT-5 Nano up to 128,000 tokens.

Which can read images, PDFs, audio or video?

DeepSeek-V3.1 accepts text; GPT-5 Nano accepts text and images. GPT-5 Nano handles the widest range of inputs.

Are any of these open source?

DeepSeek-V3.1 publishes its weights (MIT License) and can be self-hosted; GPT-5 Nano is proprietary.

Which is newer?

DeepSeek-V3.1 is the newest, released Aug 21, 2025. GPT-5 Nano came out Aug 7, 2025. Knowledge cutoff: GPT-5 Nano May 30, 2024.

How do you decide the winner?

Each model gets a 0–100 score on capability (50%, independent benchmark results); price (25%, blended price per million tokens (3 input : 1 output), log scale); inputs & features (15%, image, PDF, audio and video input, tool calling, structured output and reasoning); context window (10%, maximum tokens per request, log scale). Dimensions missing for any model are dropped and the remaining weights rescaled, so every model is judged on the same evidence. Specs and prices come from public model listings and the labs’ own API pages; capability scores come from independent benchmark runs. Data updated Oct 4, 2026.

05 — Keep comparing

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